Method and apparatus for determining implant positions of two medical implant components forming a joint

ABSTRACT

A data processing method, performed by a computer, for determining implant positions of two implant components relative to two bones, wherein each of the implant components is to be attached to one of the bones such that the implant components form a joint between the bones, and wherein an implant position is a relative position between the implant component and the corresponding bone, said method comprising the steps of:a) acquiring a set of target poses, wherein a target pose represents a relative position to be achieved between the two bones;b) calculating a set of virtual poses for a pair of virtual test implant positions, wherein the set of virtual poses comprises one virtual pose for each of the target poses and wherein a virtual pose represents a relative position between the two bones if the virtual test implant positions were applied as the implant positions;c) calculating a pose deviation value for each of the target poses, wherein a pose deviation value represents the difference between a target pose and the corresponding virtual pose;d) calculating an overall pose deviation value from all the individual pose deviation values;e) repeating steps b) to d) for different pairs of virtual test implant positions until the overall pose deviation value fulfils a minimisation criterion; andf) using the pair of virtual test implant positions for which the minimisation criterion is fulfilled as the implant positions.

The present invention relates to a method and a device for determiningimplant positions of two implant components relative to two bones.

Replacing worn joints between two bones with artificial joints hasbecome a standard medical procedure. In a typical approach, the parts ofthe two bones forming the original joint are removed and replaced withtwo implant components which interact with each other. An importantfactor in the success of the replacement, i.e. a correct kinematicfunctioning of the joint after the replacement, is that of finding asuitable position of the implant components relative to the bones whichthey are attached to. While this document focusses on knee joints, thepresent invention is equally applicable to other joints such as theelbow joint.

The relative position between an implant component and a bone isrepresented by six parameters corresponding to six degrees of freedom.These six degrees of freedom consist of three translational degrees offreedom and three rotational degrees of freedom. The directions of thetranslational degrees of freedom are preferably the proximodistal (pd)direction, the anterioposterior (ap) direction and the mediolateral (ml)direction, and the three rotational degrees of freedom are preferablyrepresented by the flexion/extension (fe) angle, the internal/external(ie) angle and the varus/valgus (vv) angle. The positions of the twoimplant components are thus defined by twelve parameters for twelvedegrees of freedom hence finding suitable implant positions meansfinding suitable values for these twelve parameters.

In a classic planning approach for computer assisted navigated totalknee replacement, the implant components are rotationally aligned tobasic bone directions and shifted into place. Each implant componentposition is established independently of the other, i.e. onlyconsidering the bone geometry and bone shape. Classic planning canresult in poor kinematics of the joint after the replacement. Poorkinematics can cause problems for the patient, i.e. flexion andextension deficits of the postoperative joint, looseness or excessivestress for the ligaments as well as excessive wear of the implantcomponents.

A more sophisticated approach is commonly referred to as the legalignment approach. It aims to adapt the implant positions to thefreedom and limits provided by the soft tissue, for example the cruciateand collateral ligaments. Two poses are used to individually optimisethree dedicated position parameters. Typically, full extension and 90°of flexion are used as the two poses. For the tibial implant, the shiftin the proximodistal direction (“pd shift”) is adjusted. For the femoralimplant, the shift in the anterioposterior direction (“ap shift”) andthe internal-external rotation (“ie rotation”) are adjusted. A “pose” isa relative position between the two bones. The leg alignment approach ishowever limited in several aspects, one being that it only optimisesthree of the degrees of freedom of the implant positions.

In a first step with the knee joint at full extension, the femur and thetibia are actively aligned with their mechanical axes so as to fall inline. The surgeon manually applies a corrective force to the bones. As aresult, the ligaments are stretched and the joint gap, i.e. the gapbetween the two bones within the joint, opens up on the side with thedominant bone loss. The planned tibial component position is shifted inthe proximodistal direction until it touches the femoral implant in thealigned bone pose.

In a second step at a 90° flexion of the knee joint, the ap shift andthe ie rotation of the planned femoral implant position are adjusted forparallel alignment and contact between the femoral implant and thetibial implant. The shift and rotations are calculated on the basis ofimplant thickness values provided by the implant manufacturer and themeasurement of both the established poses in all or dedicated degrees offreedom.

In this document, the inventor proposes an improved planning approach asdescribed in the independent claims. Advantageous embodiments aredefined in the dependent claims.

The present invention relates to a data processing method, performed bya computer, for determining implant positions of two implant componentsrelative to two bones, wherein each of the implant components is to beattached to one of the bones such that the implant components form ajoint between the bones, and wherein an implant position is a relativeposition between the implant component and the corresponding bone. Inthis document, the term “position” means a spatial location in up tothree translational dimensions and/or a rotational alignment in up tothree rotational dimensions.

A first step of the method involves acquiring a set of target poses,wherein a target pose represents a relative position to be achievedbetween the two bones. The target poses can be provided using a numberof approaches. In a first approach, sample poses of the two bones arerecorded before joint replacement. In another approach, sampled poses ofa corresponding joint are mirrored, wherein sampled poses of the rightleg can for example be mirrored in order to be used as target poses forthe left leg, and vice versa. In yet another approach, the target posesare hypothetical or predefined poses which represent the desired orideal kinematics of the joint.

A second step of the method involves calculating a set of virtual posesfor a pair of virtual test implant positions, wherein the set of virtualposes comprises one virtual pose for each of the target poses andwherein a virtual pose represents a relative position between the twobones that provides the intended mechanical interaction of the implantcomponent surfaces, i.e. by having stable contact, and wherein theimplant components are placed at the set of virtual test implantpositions. In other words, the virtual test implant positions areassumed for the implant components. The virtual poses represent therelative positions between the two bones if the implant components wereimplanted using the assumed virtual test implant positions and interactin their mechanically intended way. The mechanically intended way ofinteraction in particular requires stable implant component contactwithout overlap or gap.

A virtual pose shall approximate the real pose that the joint wouldescape to with the implant components implanted and the target poseapplied. The real pose depends, besides the implant positions, on thetarget pose, on the shape of the implant components and on themechanical interaction of all the bony and the soft tissue structures,such as ligaments, tendons and muscles, of the joint. The virtual posecan be determined considering all possible factors as mentioned above orby using a simplified approach with a reduced set of factors asexplained below in more detail.

Calculating a virtual pose in particular can comprise some sort ofmodelling the behaviour of the bony and soft tissue structures. Inparticular, the potential position changes from the target pose to thevirtual pose can be restricted to dedicated degrees of freedom toestablish preferred elongation directions of ligaments or muscle fibres.While, in general, many virtual poses might exist for a pair of virtualtest implant positions and a target pose, this restriction preferablyresults in just one virtual pose.

A third step of the method involves calculating a pose deviation valuefor each of the target poses, wherein a pose deviation value representsthe difference between a target pose and the corresponding virtual pose.This means that the pose deviation value indicates the degree ofsimilarity between a target pose and the corresponding virtual pose fora particular pair of virtual test implant positions.

A fourth step involves calculating an overall pose deviation value fromall the individual pose deviation values. The overall pose deviationvalue therefore represents the degree of similarity for all the targetposes and all the virtual poses and is thus an indicator for the overallappropriateness of the assumed pair of virtual test implant positions.

In a fifth step, the second to fourth steps are repeated for differentpairs of virtual test implant positions until the overall pose deviationvalue fulfils a minimisation criterion.

In other words, the best possible pair of virtual test implant positionsis determined. The minimisation criterion can be a simple thresholdvalue, such that iteration is discontinued once the overall posedeviation value for a particular pair of test implant positions fallsbelow the threshold value. Alternatively, the minimisation criterion canbe a minimum, such as a local minimum or preferably a global minimum.This means that the steps are repeated until, for a particular set ofpairs of virtual test implant positions, the pair of test implantpositions for which the overall pose deviation value is a minimum isfound.

A sixth step involves using the pair of virtual test implant positionsfor which the minimisation criterion is fulfilled as the implantpositions, in particular as the final implant positions for a surgicaltherapy plan. This pair then represents the preferred implant positionwhich will achieve the greatest congruency of target and virtual boneposes and which result in the best possible kinematic properties of thejoint.

In accordance with the present invention, a plurality of target posesare used to determine the implant positions. The set of target posespreferably comprises at least three poses, even more preferably at least5, 10, 15, 20 or more poses. Using this approach, the kinematics of thejoint can be optimised over its whole range of motion (ROM) instead offor full extension and 90° flexion only, as with the leg alignmentapproach. In addition, the leg alignment approach only considers threedegrees of freedom for the two components together, whereas the theinvention can optimise any desired number of degrees of freedom for theimplant positions which actually have twelve degrees of freedom (sixdegrees of freedom for one implant component and six degrees of freedomfor the other implant component). Moreover, the parameters for thedegrees of freedom considered are not determined one after the other butrather jointly, which respects potential interdependencies of theimplant positions.

As described above, a virtual pose represents the relative positionbetween the two bones, assuming the implant components are attached tothe bones in the corresponding virtual test implant positions. A virtualpose is a pose which the two bones would actually assume, i.e. afunctional pose involving a specific contact between the implantcomponents. In the case of a knee joint, such contact is achieved whenthe condyles of the femoral implant are in stable contact with thecorresponding plateaus of the tibial implant. In the method according tothe present invention, calculating a virtual pose therefore preferablyinvolves determining a relative position between the implant componentsin which they are in stable contact. As indicated above, stable contactapplies when the two implant components are in contact at at least twocontact points. It will be obvious that said relative position betweenthe implant components must correspond to a natural pose of the bones,i.e. a pose which is within the regular functional range of the joint.

As outlined above, a virtual pose is a relative position and istherefore defined by up to six parameters corresponding to six degreesof freedom, namely up to three translational degrees of freedom and upto three rotational degrees of freedom.

As explained above, the position of an implant component relative to thebone has six degrees of freedom. The relative position of the implantcomponent has to be defined with respect to a reference of the bone,such as a co-ordinate system of the bone, which is also referred to as abone co-ordinate system. The bone co-ordinate system is preferably aCartesian co-ordinate system. The location of the origin of a boneco-ordinate system and the orientation of its axes can generally beselected arbitrarily. However, it is preferable to align the axes of thebone co-ordinate system so as to be parallel with anatomical bone axessuch as for example the mechanical axis. Preferably, one axis of theco-ordinate system extends in a proximodistal direction (“pddirection”), which for example equates with the mechanical axis of afemur or a tibia, while another axis extends in the mediolateraldirection (“ml direction”) and yet another axis extends in theanterioposterior direction (“ap direction”). A rotation about theproximodistal axis (“pd axis”) is an internal/external rotation (“ierotation”), a rotation about the mediolateral axis (“ml axis”) is aflexion/extension rotation (“fe rotation”), and a rotation about theanterioposterior axis (“ap axis”) is a varus/valgus rotation (“vvrotation”). The absolute location of the origin of the bone co-ordinatesystem is irrelevant, although the origin has to be kept constant withrespect to the bone.

Using a bone co-ordinate system as described above, the position of animplant component can be described by six parameters which can becombined into a vector. In the case of a knee joint, the position of thetibial implant can be described by pos_(tibia)=(ml_(t), ap_(t), pd_(t),vv_(t), ie_(t), fe_(t))^(T) and the position of the femoral implant canbe described by pos_(femur)=(ml_(f), ap_(f), pd_(f), vv_(f), ie_(f),fe_(f))^(T). A pose, i.e. a relative position between the two bones, canalso be described by six parameters for the six degrees of freedom. Apose is preferably represented by the relative position of a co-ordinatesystem of one of the bones in the co-ordinate system of the other bone.These two co-ordinate systems of the bones are preferably the same boneco-ordinate systems as those used to describe the implant componentpositions, though they need not be.

Preferably, each implant component also has a co-ordinate systemassigned to it as a reference; these co-ordinate systems are alsoreferred to as implant co-ordinate systems. The implant position of oneimplant component relative to the corresponding bone can then beexpressed as the relative position between the bone co-ordinate systemand the implant co-ordinate system. The implant co-ordinate systems arepreferably Cartesian co-ordinate systems, the axes of which preferablymatch the ml, ap and pd directions, in particular those locally assignedto the implant component. The relative position between a boneco-ordinate system and an implant co-ordinate system can be described bya transformation, such as a vector comprising the six parameters asdescribed above or a 4×4 transformation matrix. For example, a matrix Fdescribes the transformation of the femoral bone co-ordinate system intothe femoral implant co-ordinate system, and a matrix T describes atransformation of the tibial bone co-ordinate system into the tibialimplant co-ordinate system.

In one embodiment, a pose is represented by the relative position of theimplant co-ordinate systems. The transformation matrices F and T areknown and constant for a given pair of implant positions. A poserepresented by a transformation matrix B which represents thetransformation of one bone co-ordinate system into the other boneco-ordinate system can then be used to calculate a transformation matrixJ which describes the pose between the two implant co-ordinate systems.For the same pose B, the transformation matrix J depends on the implantpositions, i.e. the matrices F and T and can be calculated as J=F*B*T⁻¹.A set of target poses represented by a set of transformation matrices Bcan therefore also be expressed as a set of target poses represented bytransformation matrices J for fixed transformation matrices F and T.

In other words, a pose represented by the relative position of the(bone) co-ordinate systems which are not co-ordinate systems of theimplant components is transformed into a pose represented by therelative position of the co-ordinate systems of the implant components.In this document, a pose can be a bone pose or a joint pose, dependingon the references used. A target pose can thus be a target bone pose ora target joint pose and a virtual pose can be a virtual bone pose or avirtual joint pose.

The transformation J describes the relative position between the twoimplant components and can therefore be referred to as the implant pose.The implant pose J is not necessarily a pose in which the two implantcomponents are in stable contact.

For each of the target joint poses J, a corresponding virtual joint poseJ′ therefore has to be found in which the implant components are inparticular in stable contact. A virtual implant pose J′ can beconverted, via the transformations F and T, into a bone pose B′ which isa virtual bone pose. Since the implant co-ordinate systems are assignedto the implants and are therefore very close to the joint, thedifference between a target joint pose J and the corresponding virtualjoint pose J′ can easily be interpreted by a physician because itrepresents meaningful values of the joint kinematics expressed as shiftsalong and rotations around main physiological directions. Transforming abone pose into a joint pose or vice cersa is explained in detail inpatent application PCT/EP2011/072324, which is hereby incorporated byreference.

There are a number of different possible ways of finding a virtual posethat provides the intended mechanical interaction of the implantcomponent surfaces, i.e. by having stable contact. One basic approach isto simply test a plurality of poses until a suitable pose is found.However, a multitude of more sophisticated approaches also exist.

In one embodiment, all but two parameters are fixed and the remainingtwo parameters are varied until a stable contact is achieved. If, inparticular, a virtual pose, and preferably a virtual joint pose, isdefined by six parameters corresponding to six degrees of freedom, thencalculating a virtual pose involves fixing four of the six parametersand varying the remaining two parameters until a stable contact isachieved. In a particular embodiment, the parameters for the ml shift,the ap shift, the ie rotation and the fe rotation are fixed and theparameters for the pd shift and the vv rotation are determined. Thisapproach is advantageous in that it obtains a virtual pose, inparticular a virtual bone pose, which very likely matches the pose thebones would actually take if the implants were attached to the boneswith the corresponding pair of test implant positions, in particularsince the ligaments create a force between the bones which mainly causesa pd movement and a moment which results in a w rotation.

More details regarding this approach are described in the patentapplication PCT/EP2012/061757, which is hereby incorporated byreference. In this document, one approach involves selecting an initialrelative position and bringing the two bones together translationallyuntil they are in contact at a first contact point. The approach is thencontinued until there is a contact at a second contact point. Thedistance in the direction of approach between the first and secondcontact points is used to determine a rotation such that the two bonesare in stable contact. In an alternative approach, the first contactpoint is determined, and one of the bones is then rotated about thefirst contact point until there is stable contact between the two bones.In both approaches, values for the parameters in one rotational degreeof freedom and one translational degree of freedom are determined forconstant values of the other parameters. This approach is preferablyapplied if a virtual joint pose is determined, because a virtual jointpose is based on physiologically meaningful directions close to thejoint as explained above.

Another approach for calculating a virtual pose is disclosed in thepatent application PCT/EP2011/072323, which is also hereby incorporatedby reference. In this approach, a plurality of poses in which two bonesare in stable contact are given. A virtual pose, for example for aparticular flexion angle, is then determined from the known poses, forexample by interpolation or extrapolation. This approach, too, ispreferably applied if a virtual joint pose is determined, becausedetermining the virtual joint pose is mostly independent of the virtualtest implant positions. This is because stable contact depends on theshape of the implants rather than their positions relative to the bones.This means that only one set of poses in which the two bones are instable contact is required which can be interpolated or extrapolated.

As explained above, one step of the method involves calculating a posedeviation value for each of the target poses. A pose deviation value isa single numerical value assigned to the particular difference between atarget pose B and a virtual pose B′ or equally between a target implantpose J and a virtual implant pose J′. The computational rule forcalculating a pose deviation value from the difference between a targetpose and a virtual pose, which also comprises up to six parameters forthe six degrees of freedom, is not particularly limited and can beselected as appropriate. Calculating the pose deviation value can forexample involve weighting the parameters.

In one embodiment, which is particularly relevant in combination withcalculating a virtual pose using four fixed parameters and determiningone translational and one rotational parameter as described above, thepose deviation value is calculated from the deviation between a virtualpose and a corresponding target pose, and preferably between a virtualjoint pose and a corresponding target joint pose, with respect to avarus-valgus rotation (“vv rotation”) and a proximodistal shift (“pdshift”) only. Since the other four parameters are constant, they can bedisregarded when calculating the pose deviation value. A pose deviationvalue can then in particular be calculated using the equation

poseDeviationValue=[(pd _(J) −pd _(J′))²+(vv _(J) −vv _(J′))²]^(1/2).

In another embodiment, a pose deviation value is calculated from thedistances between each of two points on one of the bones andcorresponding points on the other bone. In the case of a knee joint,these four points on the two bones are the points at which thecollateral ligaments are connected to the bones. The points at which theligaments are connected to the femur can be approximated as being theepicondylar points of the femur. A pose deviation value can then becalculated in an alternative fashion from the distances between each ofthe two epicondylar points and a transverse plane which extends throughthe tibia, in particular using the equation

poseDeviationValue=[(epiM_(J)−epiM_(J′))²+(epiL_(J)−epiL_(J′))²]_(1/2),

where epiM is the distance between the medial epicondyle of the femurand the transverse plane, epiL is the distance between the lateralepicondyle of the femur and the transverse plane, and J and J′ areindices for the target pose and the virtual pose, respectively. Eventhough J and J′ are used as indices, the target pose and the virtualpose need not be a target joint pose and a virtual joint pose, but couldlikewise be a target bone pose and a virtual bone pose.

Calculating the overall pose deviation value from all the individualpose deviation values can involve calculating the sum of the posedeviation values or the square root of the sum of the squares of thepose deviation values. In one embodiment, the overall pose deviationvalue is calculated from weighted pose deviation values. In thisembodiment, the influence of particular poses can be reduced oremphasised. Preferably, at least one of the weightings is not 1.

The virtual test implant positions can generally be chosen arbitrarily,i.e. any virtual test implant position which satisfies the minimisationcriterion can be selected, even though it may represent a surgically orphysiologically undesirable position at the bone. In one embodiment ofthe present invention, boundaries are therefore defined for the virtualtest implant positions. The boundaries are in particular defined byvalue ranges for the parameters for the six degrees of freedom of eachvirtual test implant position.

As described above, a virtual test implant position is defined by sixparameters corresponding to six degrees of freedom, thus resulting intwelve degrees of freedom for the two implant components. In oneembodiment, the virtual test implant positions are varied in less thantwelve degrees of freedom, and the parameters for the remaining degreesof freedom are set to fixed values. The parameters for the remainingdegrees of freedom can then for example be determined using the classicplanning approach or the leg alignment approach. The following listcomprises example scenarios for the degrees of freedom in which thevirtual test implant positions can be varied. In these scenarios, thevaried parameters are:

1. pd_(t), ap_(f) and ie_(f);

2. pd_(t), ap_(f), ie_(f) and pd_(f);

3. pd_(t), ap_(f), ie_(f), pd_(f) and ie_(t);

4. pd_(t), ap_(f), ie_(f), pd_(f), ie_(t) and fe_(t); and

5 pd_(t), ap_(f), ie_(f), pd_(f), ie_(t), fe_(t) and vv_(t).

The target poses can be determined from image data of the bones whichare captured for different poses of the bones using marker devices whichare attached to the bones and tracked using a medical navigation systemor any other suitable approach.

The present invention also relates to a program which, when running on acomputer, causes the computer to perform the steps of the method asdescribed above and/or to a program storage medium on which the programis stored and/or to a computer comprising such a program storage mediumand/or to a signal wave, in particular a digital signal wave, carryinginformation which represents the program.

The present invention also relates to a device for determining implantpositions of two implant components relative to two bones, comprising acomputer onto which the program as described above is loaded.

The method in accordance with the invention is in particular a dataprocessing method. The data processing method is preferably performedusing technical means, in particular a computer. The data processingmethod is preferably constituted to be executed by or on a computer andin particular is executed by or on the computer. In particular, all thesteps or merely some of the steps (i.e. less than the total number ofsteps) of the method in accordance with the invention can be executed bya computer. The computer in particular comprises a processor and amemory in order to process the data, in particular electronically and/oroptically. The calculating steps described are in particular performedby a computer. Determining steps or calculating steps are in particularsteps of determining data within the framework of the technical dataprocessing method, in particular within the framework of a program. Acomputer is in particular any kind of data processing device, inparticular electronic data processing device. A computer can be a devicewhich is generally thought of as such, for example desktop PCs,notebooks, netbooks, etc., but can also be any programmable apparatus,such as for example a mobile phone or an embedded processor. A computercan in particular comprise a system (network) of “sub-computers”,wherein each sub-computer represents a computer in its own right. Theterm “computer” includes a cloud computer, in particular a cloud server.The term “cloud computer” includes a cloud computer system which inparticular comprises a system of at least one cloud computer and inparticular a plurality of operatively interconnected cloud computerssuch as a server farm. Such a cloud computer is preferably connected toa wide area network such as the world wide web (WWW) and located in aso-called cloud of computers which are all connected to the world wideweb. Such an infrastructure is used for “cloud computing”, whichdescribes computation, software, data access and storage services whichdo not require the end user to know the physical location and/orconfiguration of the computer delivering a specific service. Inparticular, the term “cloud” is used in this respect as a metaphor forthe Internet (world wide web). In particular, the cloud providescomputing infrastructure as a service (IaaS). The cloud computer canfunction as a virtual host for an operating system and/or dataprocessing application which is used to execute the method of theinvention. The cloud computer is for example an elastic compute cloud(EC2) as provided by Amazon Web Services™. A computer in particularcomprises interfaces in order to receive or output data and/or performan analogue-to-digital conversion. The data are in particular data whichrepresent physical properties and/or which are generated from technicalsignals. The technical signals are in particular generated by means of(technical) detection devices (such as for example devices for detectingmarker devices) and/or (technical) analytical devices (such as forexample devices for performing imaging methods), wherein the technicalsignals are in particular electrical or optical signals. The technicalsignals in particular represent the data received or outputted by thecomputer. The computer is preferably operatively coupled to a displaydevice which allows information outputted by the computer to bedisplayed, for example to a user. One example of a display device is anaugmented reality device (also referred to as augmented reality glasses)which can be used as “goggles” for navigating. A specific example ofsuch augmented reality glasses is Google Glass (a trademark of Google,Inc.). An augmented reality device can be used both to input informationinto the computer by user interaction and to display informationoutputted by the computer.

The expression “acquiring data” in particular encompasses (within theframework of a data processing method) the scenario in which the dataare determined by the data processing method or program. Determiningdata in particular encompasses measuring physical quantities andtransforming the measured values into data, in particular digital data,and/or computing the data by means of a computer and in particularwithin the framework of the method in accordance with the invention. Themeaning of “acquiring data” also in particular encompasses the scenarioin which the data are received or retrieved by the data processingmethod or program, for example from another program, a previous methodstep or a data storage medium, in particular for further processing bythe data processing method or program. The expression “acquiring data”can therefore also for example mean waiting to receive data and/orreceiving the data. The received data can for example be inputted via aninterface. The expression “acquiring data” can also mean that the dataprocessing method or program performs steps in order to (actively)receive or retrieve the data from a data source, for instance a datastorage medium (such as for example a ROM, RAM, database, hard drive,etc.), or via the interface (for instance, from another computer or anetwork). The data can be made “ready for use” by performing anadditional step before the acquiring step. In accordance with thisadditional step, the data are generated in order to be acquired. Thedata are in particular detected or captured (for example by ananalytical device). Alternatively or additionally, the data are inputtedin accordance with the additional step, for instance via interfaces. Thedata generated can in particular be inputted (for instance into thecomputer). In accordance with the additional step (which precedes theacquiring step), the data can also be provided by performing theadditional step of storing the data in a data storage medium (such asfor example a ROM, RAM, CD and/or hard drive), such that they are readyfor use within the framework of the method or program in accordance withthe invention. The step of “acquiring data” can therefore also involvecommanding a device to obtain and/or provide the data to be acquired. Inparticular, the acquiring step does not involve an invasive step whichwould represent a substantial physical interference with the body,requiring professional medical expertise to be carried out and entailinga substantial health risk even when carried out with the requiredprofessional care and expertise. In particular, the step of acquiringdata, in particular determining data, does not involve a surgical stepand in particular does not involve a step of treating a human or animalbody using surgery or therapy. In order to distinguish the differentdata used by the present method, the data are denoted (i.e. referred to)as “XY data” and the like and are defined in terms of the informationwhich they describe, which is then preferably referred to as “XYinformation” and the like.

In particular, the invention does not involve or in particular compriseor encompass an invasive step which would represent a substantialphysical interference with the body requiring professional medicalexpertise to be carried out and entailing a substantial health risk evenwhen carried out with the required professional care and expertise. Inparticular, the invention does not comprise a step of positioning amedical implant in order to fasten it to an anatomical structure or astep of fastening the medical implant to the anatomical structure or astep of preparing the anatomical structure for being fastened to themedical implant. More particularly, the invention does not involve or inparticular comprise or encompass any surgical or therapeutic activity.For this reason alone, no surgical or therapeutic activity and inparticular no surgical or therapeutic step is necessitated or implied bycarrying out the invention.

In the following, example embodiments of the invention are describedwith reference to the figures which illustrate the invention merely byway of example and do not limit the scope of the invention to thespecific embodiments illustrated, and which show:

FIG. 1 a plurality of poses for different implant positions;

FIG. 2 a block diagram illustrating a process for determining theimplant positions;

FIGS. 3 a, 3 b a single pose of the joint, viewed from two directionsperpendicular to one another;

FIGS. 4 a to 4 c the transformation of a bone pose into an implant pose;

FIG. 5 a virtual pose;

FIG. 6 steps for determining a virtual bone pose for a target bone pose;

FIG. 7 a first example of calculating a pose deviation value;

FIG. 8 a second example of determining a pose deviation value;

FIG. 9 a computer for carrying out the method according to theinvention;

FIGS. 10 a, 10 b graphs showing deviations between target poses andvirtual poses determined using the classic planning, leg alignment andthe present invention, respectively, over the range of motion; and

FIG. 11 comparative results for the implant position results for the legalignment approach and the approach in accordance with the presentinvention.

The left-hand illustration in FIG. 1 shows a plurality of bone poses,wherein a bone pose is a relative position between two bones. FIG. 1illustrates the overall working principle of the invention. In thepresent example, the two bones are a femur 1 and a tibia 2 and the boneposes correspond to different flexion angles of the knee joint whichconnects the femur and the tibia. The femur 1 comprises a femoralimplant component 3, and the tibia 2 comprises a tibial implantcomponent 4. The implant components form an artificial knee joint. Theimplant positions shown in the left-hand illustration in FIG. 1represent a classic approach. The bone poses represent example targetbone poses, which are for example poses which the knee joint assumedprior to the introduction of an artificial knee joint.

As can be seen from FIG. 1 , there are some poses in which there wouldbe a gap between the femoral implant 3 and the tibial implant 4, andsome poses in which the implants would overlap each other, once theimplant components had been attached. In the latter case, the boneswould move away from each other since such an overlap is not possible inreality. This would result in a loose knee joint in the poses exhibitinga gap, and a significant stress on the ligaments in the poses exhibitingoverlapping implants. The gaps and overlaps between the implantcomponents 3 and 4 in FIG. 1 , and in particular in the left-handillustration in FIG. 1 , are exaggerated in order to accentuate theeffect of the present invention.

The right-hand illustration in FIG. 1 represents the femur 1 and thetibia 2, together with the attached femoral implant component 3 and theattached tibial implant component 4, for the same poses as in theleft-hand illustration, but with optimised implant positions. It can beseen that there are only small gaps or overlaps between the implantcomponents, which means that the kinematics of the original knee jointare matched quite well.

FIG. 2 shows a block diagram which illustrates an approach fordetermining the implant positions. The diagram includes an adding block5, an optimisation block 6 and a prediction block 7. A set of targetposes is fed into the adding block 5 and the prediction block 7. Theprediction block 7 calculates a set of virtual poses for a pair ofvirtual test implant positions. The set of virtual poses comprises onevirtual pose for each of the target poses. A virtual pose is ahypothetical pose for a particular pair of implant positions. A virtualpose is a pose in which the implant components 3 and 4 are in stablecontact, which means that they are in contact at at least two points. Inother words, a virtual pose is a pose into which the joint, and thus thebones, are forced due to the mechanical interaction of the implantcomponents when they are placed at the assumed pair of virtual testimplant positions.

In a first iteration, the prediction block 7 uses an initial pair ofvirtual test implant positions which can comprise arbitrary virtual testimplant positions or pre-calculated virtual test implant positions. Aset of virtual poses is then provided to the adding block 5, where eachvirtual pose is subtracted from its corresponding target pose, thusresulting in a set of difference poses between the target poses and thevirtual poses. This set of difference poses is provided to theoptimisation block 6 which calculates a pose deviation value for each ofthe target poses, wherein a pose deviation value represents a singlenumeric value corresponding to the difference between a target pose andthe corresponding virtual pose.

The optimisation block 6 calculates an overall pose deviation value fromthe plurality of individual pose deviation values. If this overall posedeviation value fulfils a predetermined minimisation criterion, then theset of virtual test implant positions used by the prediction block 7 isoutputted as the implant positions. If the overall pose deviation valuedoes not fulfil the minimisation criterion, the optimisation block 6determines a new pair of virtual test implant positions which is thenprovided to the prediction block 7 in order to calculate a new set ofvirtual poses.

The optimisation block 6 can select the new pair of virtual test implantpositions by sequentially selecting pairs of virtual test implantpositions from a list of pairs of virtual test implant positions.Alternatively, however, the optimisation block 6 can also implement anoptimisation algorithm which determines the new pair of virtual testimplant positions from at least one of the overall pose deviation valuescorresponding to the previously analysed pairs of virtual test implantpositions.

FIGS. 3 a and 3 b show the femur 1 and the tibia 2 in a particular posein a frontal and a lateral view, respectively. As can be seen from FIGS.3 a and 3 b , a femoral co-ordinate system 8 is assigned to the femur 1,and a tibial co-ordinate system 9 is assigned to the tibia 2. Theco-ordinate systems 8 and 9, which are also referred to as boneco-ordinate systems, have an invariable location and orientationrelative to the respective bones which they are assigned to. In thisexample embodiment, the orientations of the bone co-ordinate systems 8and 9 is such that their y-axis extends in a proximodistal direction,their x-axis extends in a mediolateral direction, and their z-axisextends in an anterioposterior direction when the leg is in its neutralposition. FIGS. 3 a and 3 b also show the mechanical axis 10 of thefemur 1 and the mechanical axis 11 of the tibia 2.

As can be seen from FIGS. 3 a and 3 b , the bone pose—i.e. the relativeposition between the femur 1 and the tibia 2—can be expressed as atransformation B which transforms the femoral co-ordinate system 8 intothe tibial co-ordinate system 9 or vice versa. The transformation B canalso be referred to as the bone pose B and is preferably one of thetarget poses from the set of target poses.

FIG. 4 a shows the bones 1 and 2 from FIG. 3 a , with the femoralimplant component 3 and the tibial implant component 4 attached, for anassumed pair of virtual test implant positions. For the target bone poseB shown in FIG. 4 a , the implant components 3 and 4 would overlap eachother on the left side and provide a gap on the right side, thusresulting in an technically impossible and physiologically undesiredpose if the implant components 3 and 4 were attached using the assumedpair of virtual test implant positions. The relative position betweenthe femur 1 and the tibia 2 therefore has to be amended such that thefemoral implant 3 and the tibial implant 4 are in stable contact at atleast two contact points. This results in a virtual bone pose whichcorresponds to one particular target bone pose and depends on theassumed pair of virtual test implant positions.

As can be seen from FIGS. 4 a and 4 b , a femoral implant co-ordinatesystem 12 is assigned to the femoral implant 3, and a tibial implantco-ordinate system 13 is assigned to the tibial implant 4. The implantcomponents 3 and 4 typically have a planar region which is to be placedonto a corresponding cutting plane of the bone to which it is to beattached. The z-axis of the implant co-ordinate systems is preferablyperpendicular to this planar region, while the x-axis extends in themediolateral direction of the implant component and the y-axis extendsperpendicular to both the z-axis and the x-axis. The origin of theimplant co-ordinate systems is preferably in the middle of therespective planar region.

The relative position between an implant component and the correspondingbone can be described by a transformation between the implantco-ordinate system and a corresponding bone co-ordinate system. FIG. 4 bshows a transformation F between the femoral implant co-ordinate system12 and the femoral bone co-ordinate system 8 and a transformation Tbetween the tibial implant co-ordinate system 13 and the tibial boneco-ordinate system 9. Since the transformations F and T are constant fora particular pair of virtual test implant positions, the bone pose B canbe converted into a joint pose J, shown in FIG. 4 c , via thetransformations F and T using the equation

J=F*B*T ⁻¹,

where J, F, B and T are defined as 4×4 matrices.

The implant pose or transformation J describes the relative positionbetween the two implant co-ordinate systems 12 and 13 for a particulartransformation B between the bone co-ordinate systems 8 and 9 and aparticular pair of virtual test implant positions. As already explainedabove, a transformation between two co-ordinate systems comprises sixparameters, namely three translational shifts and three rotations. Thesesix parameters are appropriately encoded into the 4×4 matrices J, B, Fand T.

As explained above, attaching the implant components 3 and 4 to thebones 1 and 2, respectively, using the assumed pair of virtual testimplant positions could result in an undesirable relative positionbetween the bones 1 and 2, in which the implant components 3 and 4overlap each other or are not in stable contact. The prediction block 7(FIG. 2 ) therefore determines a virtual pose which corresponds to atarget pose in which the implant components 3 and 4 are in stablecontact with each other. This results in a virtual joint pose J′ asshown in FIG. 5 . Since the transformations F and T are constant, thevirtual bone pose B′ can be calculated from J′, F and T.

In this embodiment, the approach described in patent applicationPCT/EP2012/061757 is applied in order to determine a virtual joint poseJ′ which is then transformed into the virtual bone pose B′. Theparameters for the ap shift, the ml shift, the ie rotation and the ferotation are kept constant and the parameters for the pd shift and thevv rotation are determined such that the implant components 3 and 4 arein stable contact. Details will be described below with reference toFIG. 7 .

The optimisation block 6 then calculates a pose deviation value for eachtarget pose on the basis of the difference between the target pose andthe corresponding virtual pose. It can be calculated on the basis of atarget bone pose and a virtual bone pose or on the basis of a targetjoint pose and a virtual joint pose. The difference between a targetjoint pose J and a virtual joint pose J′ is however easier for aphysician to analyse if it is presented as deviations in the ml, ap andpd shifts and the ie, fe and vv rotations.

FIG. 6 summarises how a virtual bone pose is calculated for a targetbone pose. In step S1.1, a target bone pose is selected. In step S1.2, apair of virtual test implant positions is selected. In step S1.3, atarget joint pose is calculated from the target bone pose and the pairof virtual test implant positions. In step S1.4, a virtual joint pose inwhich the implant components are in stable contact is calculated. Instep S1.5, a virtual bone pose corresponding to the target bone pose iscalculated from the virtual joint pose and the pair of virtual testimplant positions.

FIG. 7 shows a femur 1 with a femoral implant 3 and a tibia 2 with atibial implant 4 in a target pose and a virtual pose, in order toexplain an approach for calculating a virtual pose which corresponds toa target pose. The left-hand illustration in FIG. 7 shows the bones withthe implant components for a particular pair of virtual test implantpositions in the target pose which exhibits the parameter values vv_(J)and pd_(J). The virtual test implant positions cause the implants 3 and4 to overlap each other. In this example approach, the parameters ml,ap, ie and fe are kept constant, and the pd parameter of the targetjoint pose J is changed such that there is a gap between the femoralimplant 3 and the tibial implant 4.

The bones 1 and 2 are then brought together in the pd direction untilthe femoral implant 3 and the tibial implant 4 are in contact with eachother. If there is no stable contact, i.e. only contact at a singlepoint, then the approach is continued until there is contact between thefemoral implant 3 and the tibial implant 4 at a second contact point.The distance between the first and second contact points in the pddirection is then used to calculate a vv parameter and a pd parametersuch that the femoral implant 3 is in stable contact with the tibialimplant 4 at two contact points. This results in a virtual joint pose J′which exhibits amended parameter values vv_(J′) and pd_(J′) and in whichthe other parameter values are identical to those of the target jointpose. A detailed description of this approach is given in the patentapplication PCT/EP2012/061757.

Since the target joint pose J and the virtual joint pose J′ differ onlyin their vv and pd parameter values, the pose deviation value can becalculated from the difference in these parameter values alone. Inparticular, the pose deviation value can be calculated using theequation

poseDeviationValue=[(pd _(J) −pd _(J′))²+(vv _(J) −vv _(J′))²]^(1/2).

FIG. 8 shows the femur 1 together with the femoral implant 3 and thetibia 2 together with the tibial implant 4 in a target joint pose (inthe left-hand illustration) and in a virtual joint pose (in theright-hand illustration), in order to explain another approach forcalculating the pose deviation value.

FIG. 8 shows a working plane 14 which is parallel to the plane spannedby the x-axis and the y-axis of the tibial co-ordinate system 9. In thisexample, the origin of the tibial co-ordinate system 9 lies in theworking plane 14. However, the working plane 14 can have any otherlocation as long as it is kept constant with respect to the tibia 2.

Two epicondylar points epiM and epiL are shown on the tibia 2. Thedistances between each of the epicondylar points epiM and epiL and theworking plane 14 for the target pose and the virtual pose are used tocalculate the pose deviation value. d_(med) and d_(lat) are thedistances for the target pose, and d_(med′) and d_(lat′) are thedistances for the virtual pose. The pose deviation value can then becalculated using the equation

poseDeviationValue=[(d _(med) −d _(med′))²+(d _(lat) −d_(lat′))²]_(1/2).

FIG. 9 schematically shows a system 15 for carrying out the method asdescribed above. The system comprises a computer 16 which is connectedto an input unit 20, such as a keyboard, and to a display unit 21, suchas a monitor. The computer 16 comprises a processing unit 17 which isconnected to a memory unit 18 and an interface 19. The CPU can acquiredata, such as the target poses, via the interface 19. The memory unit 18stores a program code to be executed by the processing unit 17 andoptionally also stores any data received via the interface 19. Theprocessing unit 17 is adapted to execute the code stored in the memoryunit 18, such that the processing unit 17 carries out the method stepsas described above. The processing unit 17 is in particular then adaptedto acquire the set of target poses, calculate a set of correspondingvirtual poses for a pair of virtual test implant positions, calculate apose deviation value for each target pose and calculate an overall posedeviation value from all the individual pose deviation values. Theprocessing unit 17 is also adapted to repeat these steps for differentpairs of virtual test implant positions in order to find a pair ofvirtual test implant positions for which the overall pose deviationvalue fulfils a predetermined minimisation criterion.

Information can be inputted into the computer 16 via the input unit 20,for example in order to limit the ranges of values for the pairs ofvirtual test implant positions. The display unit 21 is adapted todisplay the results determined by the processing unit 17, such as thecalculated implant positions.

FIGS. 10 a and 10 b comprise graphs showing deviations between targetposes and virtual poses determined using the classic planning (CPL), legalignment (LA) and the present invention (6dof), respectively, over therange of motion, i.e. a range of flexion angles of the knee joint. Thegraph of FIG. 10 a shows the deviations with regards to the pd shift(pdDev) and the graph of FIG. 10 b shows the deviations with regards tothe vv rotation (vvDev). More precisely, pdDev and vvDev are calculatedas pdDev=pd_(J)−pd_(J′) and vvDev=vv_(J)−vv_(J′), respectively, asexplained with reference to FIG. 7 . Results of the classic planningapproach are plotted in a dotted line, results of the leg alignmentapproach are plotted in a dashed line and results of the approachaccording to the present invention are plotted in a continuous line.

The target poses represent measured poses of the knee joint. The virtualposes represent the poses which would result if the implants would beimplanted according to the implant positions determined according to theclassic planning approach, the leg alignment approach and the approachaccording to the present invention, respectively. They can be comparedto the target poses of the knee joint over the knee joint's range ofmotion. The range of motion applied in FIGS. 10 a and 10 b yields from avariation of the flexion angle from 0 degrees to 92 degrees. The flexionangles are for example derived from the target poses.

The graphs show that no approach results in implant positions whichcause the target poses and the virtual poses to be identical over thewhole range of motion. The reason is that the shapes of the implants arenot identical to the shapes of the original bones, such that it isimpossible to achieve the original kinematics of the joint over thewhole range of motion, no matter how the implants are positioned. Forsome flexion angles, the present invention even yield worse virtualposes, i.e. larger deviations, than the leg alignment approach or theclassic planning approach. But overall, i.e. over the whole range ofmotion, the average deviations are lower than those for implantpositions determined using the classic planning approach or the legalignment approach.

FIG. 11 shows a table comprising numerical values for the twelveparameters of the implant positions in the example scenario which leadto the deviations shown in FIG. 10 . The values in the second columnhave been determined using the leg alignment approach. Initial valueshave been determined using classic planning, and the values for pd_(t),ap_(f) and ie_(f) have then been optimised. The values in the thirdcolumn have been determined using the approach according to theinvention for six degrees of freedom. This means that the values for thesix parameters pd_(t), ap_(f), ie_(f), pd_(f), ie_(t) and fe_(t) havebeen optimised as compared to the leg alignment approach, wherein theap_(f) parameter has been constrained to a small posterior range only.The fourth column shows the differences between the values obtained bythe leg alignment approach and the approach according to the invention.No values are shown in this column for parameters which have not beenoptimised.

1.-15. (canceled)
 16. A system for selecting an implant arrangement fora joint, the system comprising: a processor; and a non-transitory,computer-readable storage medium comprising instructions that, whenexecuted, cause the processor to: access one or more target poses forthe joint, each target pose comprising an arrangement of a first bone ofthe joint with respect to a second bone of the joint; assess one or moreproposed implant arrangements, each proposed implant arrangementcomprising an arrangement of a first implant component with respect tothe first bone and an arrangement of a second implant component withrespect to the second bone, wherein assessing each proposed implantarrangement comprises: determining, for each target pose, acorresponding pose comprising an arrangement of the first bone withrespect to the second bone based on the proposed implant arrangement andmechanical properties of at least some soft tissue associated the joint,wherein the corresponding pose comprises two or more contact pointsbetween the first implant component and the second implant component,calculating, for each target pose, a deviation score based on the targetpose and the corresponding pose, and calculating, based on the deviationscores for the one or more target poses, a composite deviation score;and select the implant arrangement from the one or more proposed implantarrangements based on the composite deviation score for each of the oneor more proposed implant arrangements.
 17. The system of claim 16,wherein the one or more target poses are based on at least one ofrecorded pre-operative poses of the first bone and the second bone ofthe joint, mirrored poses from a corresponding joint, and predefinedposes representing a desired kinematics of the joint.
 18. The system ofclaim 16, wherein selecting an implant arrangement from the one or moreproposed implant arrangements comprises selecting one of the one or moreproposed implant arrangements having a composite deviation score below apredetermined threshold value.
 19. The system of claim 16, whereinselecting an implant arrangement from the one or more proposed implantarrangements comprises selecting the proposed implant arrangement havinga minimum composite deviation score among the one or more proposedimplant arrangements.
 20. The system of claim 16, wherein determining acorresponding pose comprises determining an arrangement of the firstbone with respect to the second bone wherein the first implant componentis in stable contact with the second implant component.
 21. The systemof claim 16, wherein determining a corresponding pose comprisesadjusting one or more of a varus-valgus rotational position and aproximodistal position of the target pose.
 22. The system of claim 16,wherein the deviation score is calculated based on a deviation of one ormore of a varus-valgus rotational position and a proximodistal positionbetween the corresponding pose and the target pose.
 23. The system ofclaim 16, wherein the deviation score is based on a distance between oneor more pairs of points, wherein each pair of points comprises a pointon the first bone and a corresponding point on the second bone.
 24. Thesystem of claim 23, wherein the one or more pairs of points comprisecollateral ligament attachment points.
 25. A computer-implemented methodof selecting an implant arrangement for a joint, the method comprising:accessing one or more target poses for the joint, each target posecomprising an arrangement of a first bone of the joint with respect to asecond bone of the joint; assessing one or more proposed implantarrangements, each proposed implant arrangement comprising anarrangement of a first implant component with respect to the first boneand an arrangement of a second implant component with respect to thesecond bone, wherein assessing each proposed implant arrangementcomprises: determining, for each target pose, a corresponding posecomprising an arrangement of the first bone with respect to the secondbone based on the proposed implant arrangement and mechanical propertiesof at least some soft tissue associated with the joint, calculating, foreach target pose, a deviation score based on the target pose and thecorresponding pose, and calculating, based on the deviation scores forthe one or more target poses, an composite deviation score; andselecting the implant arrangement from the one or more proposed implantarrangements based on the composite deviation score for each of the oneor more proposed implant arrangements.
 26. The system of claim 25,wherein acquiring one or more target poses comprises at least one ofrecording pre-operative poses of the first bone and the second bone ofthe joint, mirroring a corresponding joint, and obtaining predefinedposes representing a desired kinematics of the joint.
 27. The system ofclaim 25, wherein selecting an implant arrangement from the one or moreproposed implant arrangements comprises selecting one of the one or moreproposed implant arrangements having an overall pose deviation valuebelow a predetermined threshold value.
 28. The system of claim 25,wherein selecting an implant arrangement from the one or more proposedimplant arrangements comprises selecting the proposed implantarrangement having a lowest composite deviation score among the one ormore proposed implant arrangements.
 29. The system of claim 25, whereindetermining a corresponding pose comprises determining an arrangement ofthe first bone with respect to the second bone wherein the first implantcomponent is in stable contact with the second implant component. 30.The system of claim 25, wherein determining a corresponding posecomprises adjusting one or more of a varus-valgus rotational positionand a proximodistal position of the target pose.
 31. The system of claim25, wherein the deviation score is calculated based on a deviation ofone or more of a varus-valgus rotational position and a proximodistalposition between the real pose and the target pose.
 32. The system ofclaim 25, wherein the deviation score is based on a distance between oneor more pairs of points, wherein each pair of points comprises a pointon the first bone and a corresponding point on the second bone.
 33. Thesystem of claim 32, wherein the one or more pairs of points comprisecollateral ligament attachment points.
 34. A system for assessing animplant arrangement for a joint, the system comprising: a processor; anda non-transitory, computer-readable storage medium comprisinginstructions that, when executed, cause the processor to: receiving atarget pose for the joint, the target pose comprising a relativearrangement of a first bone and a second bone of the joint; receivingthe implant arrangement, the implant arrangement comprising a relativearrangement of a first implant component and the first bone and arelative arrangement of a second implant component and the second bone;determining, for the target pose, a corresponding pose comprising arelative arrangement of the first bone and the second bone based on theimplant arrangement and mechanical properties of at least some softtissue associated with the joint, wherein the corresponding posecomprises two or more contact points between the first implant componentand the second implant component, and calculating a deviation score forthe implant arrangement based on a deviation between the target pose andthe corresponding pose.
 35. The system of claim 34, wherein determininga corresponding pose comprises determining an arrangement of the firstbone with respect to the second bone wherein the first implant componentis in stable contact with the second implant component.
 36. The systemof claim 34, wherein determining a corresponding pose comprisesadjusting one or more of a varus-valgus rotational position and aproximodistal position of the target pose.
 37. The system of claim 34,wherein the deviation score is calculated based on a deviation of one ormore of a varus-valgus rotational position and a proximodistal positionbetween the corresponding pose and the target pose.
 38. The system ofclaim 34, wherein the deviation score is based on a distance between oneor more pairs of points, wherein each pair of points comprises a pointon the first bone and a corresponding point on the second bone.
 39. Thesystem of claim 38, wherein the one or more pairs of points comprisecollateral ligament attachment points.